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Modern Stochastics: Theory and Applications


Asymptotic normality of modified LS estimator for mixture of nonlinear regressions
Volume 7, Issue 4 (2020), pp. 435–448
Pub. online: 8 December 2020      Type: Research Article      Open accessOpen Access
Received
21 August 2020
Revised
8 November 2020
Accepted
16 November 2020
Published
8 December 2020

Abstract

We consider a mixture with varying concentrations in which each component is described by a nonlinear regression model. A modified least squares estimator is used to estimate the regressions parameters. Asymptotic normality of the derived estimators is demonstrated. This result is applied to confidence sets construction. Performance of the confidence sets is assessed by simulations.

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© 2020 The Author(s). Published by VTeX
Open access article under the CC BY license.

Keywords
Finite mixture model nonlinear regression mixture with varying concentrations semiparametric estimation confidence ellipsoid

MSC2010
62J05 62G20

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